Version 1
: Received: 21 November 2018 / Approved: 23 November 2018 / Online: 23 November 2018 (14:22:33 CET)
Version 2
: Received: 5 February 2019 / Approved: 5 February 2019 / Online: 5 February 2019 (16:13:14 CET)
How to cite:
Khan, M. M. R.; Sakib, S.; Arif, R. B.; Siddique, M. A. B. Digital Image Restoration in Matlab: A Case Study on Inverse and Wiener Filtering. Preprints2018, 2018110566. https://doi.org/10.20944/preprints201811.0566.v2
Khan, M. M. R.; Sakib, S.; Arif, R. B.; Siddique, M. A. B. Digital Image Restoration in Matlab: A Case Study on Inverse and Wiener Filtering. Preprints 2018, 2018110566. https://doi.org/10.20944/preprints201811.0566.v2
Khan, M. M. R.; Sakib, S.; Arif, R. B.; Siddique, M. A. B. Digital Image Restoration in Matlab: A Case Study on Inverse and Wiener Filtering. Preprints2018, 2018110566. https://doi.org/10.20944/preprints201811.0566.v2
APA Style
Khan, M. M. R., Sakib, S., Arif, R. B., & Siddique, M. A. B. (2019). Digital Image Restoration in Matlab: A Case Study on Inverse and Wiener Filtering. Preprints. https://doi.org/10.20944/preprints201811.0566.v2
Chicago/Turabian Style
Khan, M. M. R., Rezoana Bente Arif and Md. Abu Bakr Siddique. 2019 "Digital Image Restoration in Matlab: A Case Study on Inverse and Wiener Filtering" Preprints. https://doi.org/10.20944/preprints201811.0566.v2
Abstract
In this paper, at first, a color image of a car is taken. Then the image is transformed into a grayscale image. After that, the motion blurring effect is applied to that image according to the image degradation model described in equation 3. The blurring effect can be controlled by a and b components of the model. Then random noise is added in the image via Matlab programming. Many methods can restore the noisy and motion blurred image; particularly in this paper Inverse filtering as well as Wiener filtering are implemented for the restoration purpose. Consequently, both motion blurred and noisy motion blurred images are restored via Inverse filtering as well as Wiener filtering techniques and the comparison is made among them.
Keywords
Color image, grayscale image, motion blurring, random noise, inverse filtering, Wiener filtering, restoration of an image
Subject
Computer Science and Mathematics, Probability and Statistics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.